Parametric Statistical Change Point Analysis:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Boston, MA
Birkhäuser Boston
2000
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | Recently there has been a keen interest in the statistical analysis of change point detection and estimation. Mainly, it is because change point problems can be encountered in many disciplines such as economics, finance, medicine, psychology, geology, literature, etc. , and even in our daily lives. From the statistical point of view, a change point is a place or time point such that the observations follow one distribution up to that point and follow another distribution after that point. Multiple change points problem can also be defined similarly. So the change point(s) problem is two fold: one is to decide if there is any change (often viewed as a hypothesis testing problem), another is to locate the change point when there is a change present (often viewed as an estimation problem). The earliest change point study can be traced back to the 1950s. During the following period of some forty years, numerous articles have been published in various journals and proceedings. Many of them cover the topic of single change point in the means of a sequence of independently normally distributed random variables. Another popularly covered topic is a change point in regression models such as linear regression and autoregression. The methods used are mainly likelihood ratio, nonparametric, and Bayesian. Few authors also considered the change point problem in other model settings such as the gamma and exponential |
| Beschreibung: | 1 Online-Ressource (VIII, 184 p) |
| ISBN: | 9781475731316 9781475731330 |
| DOI: | 10.1007/978-1-4757-3131-6 |
Internformat
MARC
| LEADER | 00000nmm a2200000zc 4500 | ||
|---|---|---|---|
| 001 | BV042421425 | ||
| 003 | DE-604 | ||
| 005 | 20171219 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 150317s2000 |||| o||u| ||||||eng d | ||
| 020 | |a 9781475731316 |c Online |9 978-1-4757-3131-6 | ||
| 020 | |a 9781475731330 |c Print |9 978-1-4757-3133-0 | ||
| 024 | 7 | |a 10.1007/978-1-4757-3131-6 |2 doi | |
| 035 | |a (OCoLC)858992698 | ||
| 035 | |a (DE-599)BVBBV042421425 | ||
| 040 | |a DE-604 |b ger |e aacr | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-384 |a DE-703 |a DE-91 |a DE-634 | ||
| 082 | 0 | |a 519.5 |2 23 | |
| 084 | |a MAT 000 |2 stub | ||
| 100 | 1 | |a Chen, Jie |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Parametric Statistical Change Point Analysis |c by Jie Chen, A. K. Gupta |
| 264 | 1 | |a Boston, MA |b Birkhäuser Boston |c 2000 | |
| 300 | |a 1 Online-Ressource (VIII, 184 p) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 500 | |a Recently there has been a keen interest in the statistical analysis of change point detection and estimation. Mainly, it is because change point problems can be encountered in many disciplines such as economics, finance, medicine, psychology, geology, literature, etc. , and even in our daily lives. From the statistical point of view, a change point is a place or time point such that the observations follow one distribution up to that point and follow another distribution after that point. Multiple change points problem can also be defined similarly. So the change point(s) problem is two fold: one is to decide if there is any change (often viewed as a hypothesis testing problem), another is to locate the change point when there is a change present (often viewed as an estimation problem). The earliest change point study can be traced back to the 1950s. During the following period of some forty years, numerous articles have been published in various journals and proceedings. Many of them cover the topic of single change point in the means of a sequence of independently normally distributed random variables. Another popularly covered topic is a change point in regression models such as linear regression and autoregression. The methods used are mainly likelihood ratio, nonparametric, and Bayesian. Few authors also considered the change point problem in other model settings such as the gamma and exponential | ||
| 650 | 4 | |a Statistics | |
| 650 | 4 | |a Mathematical statistics | |
| 650 | 4 | |a Statistical Theory and Methods | |
| 650 | 4 | |a Statistik | |
| 650 | 0 | 7 | |a Change-point-Problem |0 (DE-588)4598971-0 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Change-point-Problem |0 (DE-588)4598971-0 |D s |
| 689 | 0 | |8 1\p |5 DE-604 | |
| 700 | 1 | |a Gupta, A. K. |e Sonstige |4 oth | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-1-4757-3131-6 |x Verlag |3 Volltext |
| 912 | |a ZDB-2-SMA |a ZDB-2-BAE | ||
| 940 | 1 | |q ZDB-2-SMA_Archive | |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-027856842 | ||
| 883 | 1 | |8 1\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
Datensatz im Suchindex
| _version_ | 1804153094481641472 |
|---|---|
| any_adam_object | |
| author | Chen, Jie |
| author_facet | Chen, Jie |
| author_role | aut |
| author_sort | Chen, Jie |
| author_variant | j c jc |
| building | Verbundindex |
| bvnumber | BV042421425 |
| classification_tum | MAT 000 |
| collection | ZDB-2-SMA ZDB-2-BAE |
| ctrlnum | (OCoLC)858992698 (DE-599)BVBBV042421425 |
| dewey-full | 519.5 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5 |
| dewey-search | 519.5 |
| dewey-sort | 3519.5 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| doi_str_mv | 10.1007/978-1-4757-3131-6 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02957nmm a2200457zc 4500</leader><controlfield tag="001">BV042421425</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20171219 </controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">150317s2000 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781475731316</subfield><subfield code="c">Online</subfield><subfield code="9">978-1-4757-3131-6</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781475731330</subfield><subfield code="c">Print</subfield><subfield code="9">978-1-4757-3133-0</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/978-1-4757-3131-6</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)858992698</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV042421425</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">aacr</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-384</subfield><subfield code="a">DE-703</subfield><subfield code="a">DE-91</subfield><subfield code="a">DE-634</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">519.5</subfield><subfield code="2">23</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">MAT 000</subfield><subfield code="2">stub</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Chen, Jie</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Parametric Statistical Change Point Analysis</subfield><subfield code="c">by Jie Chen, A. K. Gupta</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Boston, MA</subfield><subfield code="b">Birkhäuser Boston</subfield><subfield code="c">2000</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (VIII, 184 p)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Recently there has been a keen interest in the statistical analysis of change point detection and estimation. Mainly, it is because change point problems can be encountered in many disciplines such as economics, finance, medicine, psychology, geology, literature, etc. , and even in our daily lives. From the statistical point of view, a change point is a place or time point such that the observations follow one distribution up to that point and follow another distribution after that point. Multiple change points problem can also be defined similarly. So the change point(s) problem is two fold: one is to decide if there is any change (often viewed as a hypothesis testing problem), another is to locate the change point when there is a change present (often viewed as an estimation problem). The earliest change point study can be traced back to the 1950s. During the following period of some forty years, numerous articles have been published in various journals and proceedings. Many of them cover the topic of single change point in the means of a sequence of independently normally distributed random variables. Another popularly covered topic is a change point in regression models such as linear regression and autoregression. The methods used are mainly likelihood ratio, nonparametric, and Bayesian. Few authors also considered the change point problem in other model settings such as the gamma and exponential</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Statistics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematical statistics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Statistical Theory and Methods</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Statistik</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Change-point-Problem</subfield><subfield code="0">(DE-588)4598971-0</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Change-point-Problem</subfield><subfield code="0">(DE-588)4598971-0</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="8">1\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Gupta, A. K.</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1007/978-1-4757-3131-6</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-2-SMA</subfield><subfield code="a">ZDB-2-BAE</subfield></datafield><datafield tag="940" ind1="1" ind2=" "><subfield code="q">ZDB-2-SMA_Archive</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-027856842</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">1\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield></record></collection> |
| id | DE-604.BV042421425 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T01:21:09Z |
| institution | BVB |
| isbn | 9781475731316 9781475731330 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027856842 |
| oclc_num | 858992698 |
| open_access_boolean | |
| owner | DE-384 DE-703 DE-91 DE-BY-TUM DE-634 |
| owner_facet | DE-384 DE-703 DE-91 DE-BY-TUM DE-634 |
| physical | 1 Online-Ressource (VIII, 184 p) |
| psigel | ZDB-2-SMA ZDB-2-BAE ZDB-2-SMA_Archive |
| publishDate | 2000 |
| publishDateSearch | 2000 |
| publishDateSort | 2000 |
| publisher | Birkhäuser Boston |
| record_format | marc |
| spelling | Chen, Jie Verfasser aut Parametric Statistical Change Point Analysis by Jie Chen, A. K. Gupta Boston, MA Birkhäuser Boston 2000 1 Online-Ressource (VIII, 184 p) txt rdacontent c rdamedia cr rdacarrier Recently there has been a keen interest in the statistical analysis of change point detection and estimation. Mainly, it is because change point problems can be encountered in many disciplines such as economics, finance, medicine, psychology, geology, literature, etc. , and even in our daily lives. From the statistical point of view, a change point is a place or time point such that the observations follow one distribution up to that point and follow another distribution after that point. Multiple change points problem can also be defined similarly. So the change point(s) problem is two fold: one is to decide if there is any change (often viewed as a hypothesis testing problem), another is to locate the change point when there is a change present (often viewed as an estimation problem). The earliest change point study can be traced back to the 1950s. During the following period of some forty years, numerous articles have been published in various journals and proceedings. Many of them cover the topic of single change point in the means of a sequence of independently normally distributed random variables. Another popularly covered topic is a change point in regression models such as linear regression and autoregression. The methods used are mainly likelihood ratio, nonparametric, and Bayesian. Few authors also considered the change point problem in other model settings such as the gamma and exponential Statistics Mathematical statistics Statistical Theory and Methods Statistik Change-point-Problem (DE-588)4598971-0 gnd rswk-swf Change-point-Problem (DE-588)4598971-0 s 1\p DE-604 Gupta, A. K. Sonstige oth https://doi.org/10.1007/978-1-4757-3131-6 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Chen, Jie Parametric Statistical Change Point Analysis Statistics Mathematical statistics Statistical Theory and Methods Statistik Change-point-Problem (DE-588)4598971-0 gnd |
| subject_GND | (DE-588)4598971-0 |
| title | Parametric Statistical Change Point Analysis |
| title_auth | Parametric Statistical Change Point Analysis |
| title_exact_search | Parametric Statistical Change Point Analysis |
| title_full | Parametric Statistical Change Point Analysis by Jie Chen, A. K. Gupta |
| title_fullStr | Parametric Statistical Change Point Analysis by Jie Chen, A. K. Gupta |
| title_full_unstemmed | Parametric Statistical Change Point Analysis by Jie Chen, A. K. Gupta |
| title_short | Parametric Statistical Change Point Analysis |
| title_sort | parametric statistical change point analysis |
| topic | Statistics Mathematical statistics Statistical Theory and Methods Statistik Change-point-Problem (DE-588)4598971-0 gnd |
| topic_facet | Statistics Mathematical statistics Statistical Theory and Methods Statistik Change-point-Problem |
| url | https://doi.org/10.1007/978-1-4757-3131-6 |
| work_keys_str_mv | AT chenjie parametricstatisticalchangepointanalysis AT guptaak parametricstatisticalchangepointanalysis |